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Geometric integrators and the Hamiltonian Monte Carlo method

Geometric integrators and the Hamiltonian Monte Carlo method

14 November 2017
Nawaf Bou-Rabee
J. Sanz-Serna
ArXivPDFHTML

Papers citing "Geometric integrators and the Hamiltonian Monte Carlo method"

18 / 18 papers shown
Title
Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities
Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities
Jimmy Huy Tran
T. S. Kleppe
BDL
45
0
0
25 Apr 2025
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation
Nawaf Bou-Rabee
Katharina Schuh
23
7
0
22 Aug 2023
Adaptive multi-stage integration schemes for Hamiltonian Monte Carlo
Adaptive multi-stage integration schemes for Hamiltonian Monte Carlo
Lorenzo Nagar
Mario Fernández-Pendás
J. Sanz-Serna
E. Akhmatskaya
13
1
0
05 Jul 2023
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration
Nawaf Bou-Rabee
Milo Marsden
32
12
0
20 Nov 2022
Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design,
  Case Studies
Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design, Case Studies
N. Glatt-Holtz
Andrew J Holbrook
J. Krometis
Cecilia F. Mondaini
18
10
0
10 Sep 2022
Second Order Ensemble Langevin Method for Sampling and Inverse Problems
Second Order Ensemble Langevin Method for Sampling and Inverse Problems
Ziming Liu
Andrew M. Stuart
Yixuan Wang
24
6
0
09 Aug 2022
Split Hamiltonian Monte Carlo revisited
Split Hamiltonian Monte Carlo revisited
F. Casas
J. Sanz-Serna
Luke Shaw
13
8
0
15 Jul 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive
  Agents
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
Alessandro Barp
Lancelot Da Costa
G. Francca
Karl J. Friston
Mark Girolami
Michael I. Jordan
G. Pavliotis
28
25
0
20 Mar 2022
Efficient Learning of the Parameters of Non-Linear Models using
  Differentiable Resampling in Particle Filters
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters
Conor Rosato
Vincent Beraud
P. Horridge
Thomas B. Schon
Simon Maskell
18
14
0
02 Nov 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high
  dimension
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension
Alain Durmus
A. Eberle
24
19
0
02 Aug 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions
A Unifying and Canonical Description of Measure-Preserving Diffusions
Alessandro Barp
So Takao
M. Betancourt
Alexis Arnaudon
Mark Girolami
20
17
0
06 May 2021
On explicit $L^2$-convergence rate estimate for piecewise deterministic
  Markov processes in MCMC algorithms
On explicit L2L^2L2-convergence rate estimate for piecewise deterministic Markov processes in MCMC algorithms
Jianfeng Lu
Lihan Wang
16
27
0
29 Jul 2020
Is the NUTS algorithm correct?
J. Sanz-Serna
8
0
0
04 May 2020
Cores for Piecewise-Deterministic Markov Processes used in Markov Chain
  Monte Carlo
Cores for Piecewise-Deterministic Markov Processes used in Markov Chain Monte Carlo
P. Holderrieth
17
10
0
20 Oct 2019
Coupling and Convergence for Hamiltonian Monte Carlo
Coupling and Convergence for Hamiltonian Monte Carlo
Nawaf Bou-Rabee
A. Eberle
Raphael Zimmer
77
136
0
01 May 2018
Unbiased Hamiltonian Monte Carlo with couplings
Unbiased Hamiltonian Monte Carlo with couplings
J. Heng
Pierre E. Jacob
18
63
0
01 Sep 2017
On the Geometric Ergodicity of Hamiltonian Monte Carlo
On the Geometric Ergodicity of Hamiltonian Monte Carlo
Samuel Livingstone
M. Betancourt
Simon Byrne
Mark Girolami
34
116
0
29 Jan 2016
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
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